In the rapidly evolving landscape of the 21st century, education stands at a critical crossroads. The legacy of industrial-age schooling, grounded principally in meritocratic ideals, is increasingly called into question as technological innovations, particularly artificial intelligence (AI), redefine human potential and societal needs. Today, the prevailing model—ranking and rewarding students on the basis of standardized academic performance—may no longer serve the best interests of learners or societies facing global complexity. A recent article authored by Yong Zhao of the University of Kansas and RuoJun Zhong of YEE Education, published in the ECNU Review of Education, meticulously critiques these entrenched assumptions and advances a provocative vision that reimagines educational purpose through the lens of human interdependence.
Their research foregrounds a pivotal tension in contemporary education: the longstanding adherence to meritocracy versus the emerging demands of a world shaped by AI-infused complexity. Meritocracy posits that educational success stems solely from innate ability and individual effort, a principle that has translated into systems emphasizing competition, standardized testing, and stratification. However, Zhao and Zhong expose the inadequacies of this framework, especially in light of persistent socio-economic disparities that skew the baseline opportunities available to students. Meritocratic structures, they argue, obscure critical contextual factors—family environment, resource access, and community support—that profoundly influence academic outcomes, thereby perpetuating inequality rather than mitigating it.
The authors move beyond criticism to articulate how AI technologies contest the foundational premises of traditional education. Historically, educational achievement equated with the mastery of factual knowledge and procedural skills—domains where machines have begun to excel and surpass human capacities. This development necessitates a radical pedagogical recalibration. Rather than competing with AI, learners must be empowered to engage in ‘co-agency’—collaborative partnership with intelligent systems. This conceit reframes the educational imperative, from rote memorization and standardized performance to nurturing distinctly human faculties such as creativity, ethical judgment, empathy, and collaborative problem-solving.
Central to Zhao and Zhong’s thesis is the concept of human interdependence as the new axis around which educational objectives should orbit. Unlike the meritocratic model that isolates learners into competitive silos, interdependence emphasizes relationality, collective well-being, and global citizenship. The argument holds particular urgency in an era where existential challenges—including climate change, pandemics, and geopolitical instability—cannot be addressed unilaterally. Education must therefore cultivate adaptive, empathetic individuals capable of navigating uncertainty through cooperation and shared responsibility, thereby responding effectively to complex interlocked systems.
This paradigm shift demands extensive systemic transformation. The authors advocate for dismantling uniform, age-based curricula in favor of personalized learning trajectories attuned to individual interests, contexts, and aspirations. The pedagogical environment would also move away from hierarchical cohorting and adversarial ranking, instead privileging collaborative spaces that foster mutual support and communal growth. Assessment strategies, similarly, would be revolutionized: traditional grading would give way to evaluations of personal development, social engagement, and well-being metrics, reflecting a holistic understanding of learner success.
The implications of this redefined educational paradigm extend to both policy and practice. Policymakers are challenged to reconsider accountability frameworks, resource allocation, and institutional mandates to align with principles of interdependence and co-agency. Educators, meanwhile, face the task of designing curricula and learning experiences that transcend knowledge transmission and instead nurture socio-emotional skills, ethical reasoning, and adaptive expertise compatible with AI-integrated environments. This entails ongoing professional development and cultural shifts within educational organizations.
Technically, the transition toward human interdependence involves integrative use of AI as an augmentative partner in learning processes. Intelligent tutoring systems, adaptive learning platforms, and generative AI tools can support not only personalized content delivery but also facilitate deeper collaborative interactions among learners. Leveraging these technologies responsibly requires embedding ethical frameworks and transparency in AI design, ensuring that human values such as fairness, dignity, and inclusivity guide implementation.
Moreover, the article underscores the limitations of meritocracy’s purported fairness. The reliance on standardized testing and narrow performance indicators often serves to entrench privilege by rewarding conformity over creativity and resilience. This has significant repercussions for mental health, as competitive pressures and rigid sorting mechanisms amplify stress and alienation among youth—the very populations most vulnerable to current global uncertainties. A human interdependence model aims to mitigate these harms by fostering environments where diversity is valued and collective achievement is celebrated.
Another subtle yet profound dimension of Zhao and Zhong’s scholarship is the ethical imperative embedded in the educational reconfiguration. They argue that in a hyper-connected world, moral reasoning cannot be compartmentalized or relegated to the periphery of curricula. Ethical literacy must be mainstreamed, equipping learners to grapple with dilemmas posed by AI deployment, data privacy, societal inequalities, and environmental sustainability. This emphasis on ethical education complements the broader goal of nurturing empathetic and responsible global citizens.
The timing of this scholarship is significant. As generative AI technologies rapidly mature and proliferate, the educational community faces both an existential threat and unprecedented opportunity. By redefining educational success as “becoming better with others,” Zhao and Zhong inject optimism into a discourse often dominated by apprehension regarding automation and job displacement. Their vision invites educators and stakeholders to harness AI’s transformative potential in service of human flourishing, rather than displacement.
In sum, the article serves as a clarion call to rethink education fundamentally and urgently. Zhao and Zhong’s proposition to move “From Meritocracy to Human Interdependence” challenges decades of educational orthodoxy, offering a detailed critique of existing systems alongside a compelling blueprint for future-ready schooling. Their work positions education as a social endeavor deeply embedded in relationships, empathy, and global interconnectedness, calibrated for a world where AI is an integral actor rather than an adversary. Such a shift, they contend, is not simply desirable but necessary for sustainable human progress.
This reconceptualization of education aligns with contemporary research trends emphasizing learner-centered models, social-emotional learning, and cross-disciplinary problem solving. It also resonates with broader socio-political movements advocating equity, inclusion, and collective responsibility in the face of systemic global risks. Ultimately, Zhao and Zhong’s insights map a transformative educational horizon, urging societies to pivot away from competition and toward collaboration as the hallmark of excellence.
As educational institutions grapple with these challenges, the integration of AI and human interdependence frameworks promises to cultivate learners equipped for the unforeseen complexities of the future. This entails a commitment to continuous innovation in policy, curriculum design, teacher preparation, and community engagement, ensuring that education remains a vital force for empowerment and social cohesion in an increasingly AI-permeated world.
Subject of Research: Not applicable
Article Title: From Meritocracy to Human Interdependence: Redefining the Purpose of Education
News Publication Date: 19-Jun-2025
References:
DOI: 10.1177/20965311251351988
Keywords: Education, Educational methods, Science education, Educational levels, Educational assessment, Education technology, Education policy, Educational attainment, Education research, Computer science, Artificial intelligence, Generative AI, Social sciences, Applied sciences and engineering
